title: Dynamical and Mechanistic Reconstructive Approaches of T Lymphocyte Dynamics: Using Visual Modeling Languages to Bridge the Gap between Immunologists, Theoreticians, and Programmers.
abstract: Dynamic modeling of lymphocyte behavior has primarily been based on populations based differential equations or on cellular agents moving in space and interacting each other. The final steps of this modeling effort are expressed in a code written in a programing language. On account of the complete lack of standardization of the different steps to proceed, we have to deplore poor communication and sharing between experimentalists, theoreticians and programmers. The adoption of diagrammatic visual computer language should however greatly help the immunologists to better communicate, to more easily identify the models similarities and facilitate the reuse and extension of existing software models. Since immunologists often conceptualize the dynamical evolution of immune systems in terms of "state-transitions" of biological objects, we promote the use of unified modeling language (UML) state-transition diagram. To demonstrate the feasibility of this approach, we present a UML refactoring of two published models on thymocyte differentiation. Originally built with different modeling strategies, a mathematical ordinary differential equation-based model and a cellular automata model, the two models are now in the same visual formalism and can be compared.
authors.affiliation: UPMC Univ Paris 06, UMR7211, Immunology, Immunopathology, Immunotherapy (I3), Integrative Immunology , Paris , France ; CNRS, UMR 7211, Immunology-Immunopathology-Immunotherapy (I3) Integrative Immunology , Paris , France.
authors.forename: Véronique
authors.initials: V
authors.lastname: Thomas-Vaslin
authors.forename: Adrien
authors.initials: A
authors.lastname: Six
authors.forename: Jean-Gabriel
authors.initials: JG
authors.lastname: Ganascia
authors.forename: Hugues
authors.initials: H
authors.lastname: Bersini
keywords: agent-based model; cell dynamics; complex system; computer modeling; state-transition diagram